Valuing Intrinsic and Instrumental Preferences for Privacy

54 Pages Posted: 25 Jun 2019 Last revised: 29 Feb 2020

See all articles by Tesary Lin

Tesary Lin

Boston University - Department of Marketing; University of Chicago - Marketing Management

Date Written: February 27, 2020

Abstract

In this paper, I separately measure two motives for consumers to protect privacy: an intrinsic motive, which is a “taste” for privacy; and an instrumental motive, which reflects the expected economic loss from revealing one’s private information to the firm. While the intrinsic preference is a utility primitive, the instrumental preference arises endogenously from a firm’s usage of consumer data. Combining a two-stage experiment and a structural model, I find that consumers’ intrinsic preferences for privacy range from 0 to 5 dollars per demographic variable, exhibiting substantial heterogeneity across consumers and categories of personal data. This rich heterogeneity in intrinsic preferences leads to a selection pattern that deviates from the “nothing-to-hide” argument predicted by a model with pure instrumental preferences. I then propose three strategies that firms and researchers can adopt to improve data-driven decisions when shared data are influenced by consumers’ dual privacy concerns. First, by using an experiment to measure the joint distribution of privacy preferences, firms can extrapolate selection patterns to cases where the data utilization method changes. Second, when the joint privacy preference distribution is unknown, data collection should focus on representativeness over quantity, especially when information externality is present. Lastly, firms can learn about the selection pattern in the shared data by leveraging information contained in consumers’ data-sharing decisions.

Keywords: Privacy, Revealed Preference, Information Economics, Privacy Regulation, Value of Data

JEL Classification: D01, D12, D82, D83, L11, L15, M31, M38

Suggested Citation

Lin, Tesary, Valuing Intrinsic and Instrumental Preferences for Privacy (February 27, 2020). Available at SSRN: https://ssrn.com/abstract=3406412 or http://dx.doi.org/10.2139/ssrn.3406412

Tesary Lin (Contact Author)

Boston University - Department of Marketing ( email )

United States

University of Chicago - Marketing Management ( email )

Chicago, IL 60637
United States

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